2
Associate Professor Jane Griffiths RN, BAN, MHP
Qasim Yousef Qasim Abuhantash BS, MA
Have no real or apparent conflicts of interest to report.
Conflict of Interest
3
• Learning Objectives
• Purpose
• Outline
• Background
• Environment of DHA
• Strategic Direction
• Methodology
• Improvements and Optimisation
• Innovation
• Case Studies
– Sepsis
– Suicide Assessment
• Challenges
• Outcomes
• Conclusion
• References
Agenda
4
• Discuss the benefits of an electronic medical record in providing
innovative care
• Assess how the international evidence is used as the basis for the
changes in clinical practice and culture across healthcare
• Demonstrate how DHA will guide the EMR agenda for the Emirate
of Dubai and the region
Learning Objectives
5
• His Highness Sheikh Mohammed bin Rashid Al Maktoum, Vice
President and Prime Minister of the UAE and Ruler of Dubai
called on all Dubai Government entities to embrace disruptive
innovation as a fundamental mantra of their operations and to
seek ways to incorporate its methodologies in all aspects of their
work.
• Each Government Department was to seek ways to incorporate
these methodologies in all aspects of their work
Purpose
6
• To comply with Sheikh Mohammed’s directive the Dubai Health
Authority (DHA) contracted a USA based vendor to implement an
EMR across all government health facilities in 2015.
• At the same time, the governing Board of Directors issued a
requirement that standardization of clinical practice based on
international evidence was to be implemented across all facilities
in DHA.
• The decision was made to utilize the implementation of the EMR
to facilitate the standardization of work practices across DHA and
to provide the platform for sustainable, efficient and effective
health care of the future.
Outline
7
• The EMR selected was named “Salama” (means safety in Arabic)
• Not only is it essential to engage end users in the implementation
of the EMR, it is imperative to engage these end-users with the
clinical standardization process
• Our end users understand how our health facilities work & were
already frustrated with processes that were duplicated or not
effective
Background
8
• This engagement technique ensured staff took responsibility for
their own work practices rather than using excuses such as:
– It is a decree from higher management
– It’s policy
Background
9
• 23 applications in the Enterprise system were implemented
including a patient portal
• Salama successfully went live in 2017
• 128 million existing records were migrated to the new EMR
• 2018 has seen the optimization phase for the implementation of
new initiatives
• Since then additional technology has been implemented
Background
10
• 12,000 staff are employed in DHA
– Full range of different disciplines, education levels & cultures
• 4 hospitals
• 12 Primary Health Care Centres
• 10 free standing Specialty Centres
• 18 Medical Fitness Centres
• 5 Occupational Health Centres
• 1 Nursing Home
Environment of DHA
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Strategic Direction
12
Strategic Direction
13
• The quality and safety literature identifies that 60% of our work
does not add value to the patient’s experience.
• The purpose of an EMR is to streamline services and provide
unprecedented access to information.
• DHA made the choice to use lean methodology during the
implementation phase of the EMR to ensure:
– Standardization (clinical policies)
– Elimination of waste (reduced duplication of data entry)
– Cost effective care (ensuring appropriate charges applied)
– Increase patient safety (closed loop medication
administration)
– Improve patient satisfaction (patient education provided in
Arabic)
Methodology
14
• Over 500 staff were actively involved in the standardization
process
• This technique ensured staff took responsibility for their own work
practices
• Final agreements for changes in work practices were based on
international references & best practices
• Over 500 workflows were revised & 150 policies reviewed
• Compliance and sustainability is reviewed daily/monthly
– Bar code scanning of patients and medication administration
went from 78% to 99% and has been sustained since 2017
Methodology
15
• Improvements or changes to the system use a process whereby
endusers log a “jira” ticket to the Salama Help Desk
• This ticket is allocated to the relevant application build team &
provided a prioritization code (benchmark time to resolve)
• They review the request to ensure the end-user is maximizing the
use of Salama or whether to achieve the change, the system has
to be modified
• If a change is identified then a change request is taken for review
to the relevant Governance Council (PAC, NAC, QAC, FAC,
PTAC)
• The Councils consist of senior clinical & admin staff who have
delegated authority from all facilities to authorize a change in the
build
Improvements & Optimisation
16
• In 12 months
– 27,027 Jira tickets have been raised
– 26,838 tickets have been resolved
• In addition 81 optimization changes have been built &
implemented
• 89 tip/design sheets for end-users have been developed &
implemented
• 2,502 reports have been built
• 2.1 million pts are covered in the integrated, effective EMR
implemented across DHA
Improvements & Optimisation
17
• Salama is integrated with other Dubai Government Departments
including:
– Dubai Police
– Dubai Ambulance Service
– Al Jalila Children’s Hospital
– Directorate of Residency & Foreign Affairs
– Licensing & Regulation
– Dubai Smart Government
Innovations
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• Additional technology
– Artificial Intelligence
• TB diagnosis
• Retinal scanning
• Septic shock
• Deteriorating pts
Innovations
19
• Robotics
– Medications
• Hand Held Devices
– Closed loop barcoding medication administration
• Blockchain materials management
Innovations
20
Patient by default of a high risk of fall.
• Neonates & Infants
• OT & PACU Patients
• ICU including NICU patients
• Patients in the Resuscitation area of the Emergency Department
Case Study - Falls Assessment
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• Verbal orders – emergency situation with physician present
• Telephone orders – physician outside the facility
• Delete telephone orders from the system
Case Study – Telephone Orders
22
Screening Tool
• The first level is sadness and depression levels (example of
questions that explore this level will be: How you feel, tell me
about your feeling, for the past two days did you notice change in
your feeling affected your appetite to eat, sleep, socialize..)
• The second level cover the concept of ”wish to die” (example of
questions will be: based on the positive answer in the first level,
this sad feeling make you feel that life is nothing living? Wishing to
sleep and not wake up, living is painful..
• The third level asking about suicidal attempts (example of
questions would be: based on the above did you tried or thought
to harm yourself…tried to kill yourself and if yes what you used…
• All hospitals should have action plan for the third level as per the
suicidal policy
Case Study – Suicide Assessment
23
• Validation of the tool undertaken 30 times across all hospitals,
covered different types of patients
• Nationality (Arab, Indian, Filipino, ..)
• Gender (male, female)
• Age (adult, adolescents)
• There is general acceptance from the patients to answer and to
talk about the topics been discussed
• Some patients showed more interests to talk further about their
emotional and psychological status (patients said “nobody before
talk or care about our feelings…”)
Case Study – Suicide Assessment
24
Case Study Sepsis
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• The aim is to develop an early detection system to help identify
when an inpatient’s condition will deteriorate in the future and
allow treatment/monitoring to be implemented before the
deterioration occurs.:
– Date range : 1-Dec-17 to 30-Nov-18
– Vitals data : MRN, Encounter No, Admitted time, Discharge
Time, Flowsheet name (vital signs), Reading Date/Time,
Reading Department and Specialty, Duration of Stay,
Timestamp.
– Demographic data : MRN, Encounter No, Age, Gender,
Weight, Height, and BMI.
– Response times for intervention.
– Any procedures undertaken.
– Transfer out of ICU
AI – Deteriorating Patients
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• 5921 patient encounters with 369,067 observations (average of
61 observations per encounter) were used
• The overall accuracy of the system is 89.91%.
• Risk Threshold of 0.4.
• The model needs at least 3 historical data points
• The model can predict if the patient’s health will deteriorate within
5 future time periods.
• 17.5% of all patients identified at risk of
deteriorating and who subsequently did
deteriorate were transfers out of ICU
AI – Deteriorating Patients
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• 3 previous attempts to implement an EMR had been started in
DHA
• Staff were initially cynical if this implementation would proceed &
therefore were reluctant to become engaged
• Clinical & admin practices were not standardized across DHA &
endusers all believe their own practice was “the best”
• Training & “go live” support were managed differently in each
facility
• Competition between facilities (both a challenge & an advantage)
Challenges
28
• Implementation was undertaken in 3 phases
• All sites/facilities went live within 7 months
• Successful implementation was validated by the achievement of
EMRAN & O-EMRAN Stage 6 within 8 weeks of “go live” in:
– 4 hospitals
– All PHCs
– All Specialty Centres
• Adoption and sustainability are measured daily/weekly/monthly
through reports/dashboards for individual clinicians and higher
management
Outcomes
29
• To achieve cross facility standardization required input from all
facilities & staff
• In order to reduce waste in the system, we reviewed our current
processes & implemented standardized evidence based
workflows & practices across DHA
• The review identified current inefficiencies & mistakes which were
removed/changed
• This allowed a fully integrated, effective EMR to be implemented
across DHA
Conclusion
30
• Ackerman ,J. Hemphill , R., Cowan, D (2011) Lean Is a Tool in the Toolbox, Not the Silver Bullet. Annals of
Emergency Medicine, 58, (4): 398–399
http://www.sciencedirect.com/science/article/pii/S0196064410013223#
• Atkinson P, Mukaetova-Ladinska EB. (2012) Nurse-led liaison mental health service for older adults: service
development using lean thinking methodology J Psychosom Res 72(4):328-31.
http://www.ncbi.nlm.nih.gov/pubmed/22405230
• Grove , A., Meredith J, Macintyre M, Angelis J, Neailey, K (2010) Lean implementation in primary care
health visiting services in National Health Service UK Qual Saf Health Care doi:10.1136/qshc.2009.039719
http://qualitysafety.bmj.com/content/early/2010/05/28/qshc.2009.039719.full.html
• Holder, R . (2011) Lean Thinking in emergency departments: a critical review. Annals of Emergency
Medicine 57(3):265-78. doi:10.1016/j.annemergmed.2010.08.001.
http://www.ncbi.nlm.nih.gov/pubmed/21035904
• Kollberg, B., Dahlgaard, J.J., Brehmer, P-O. (2007). Measuring lean initiatives in healthcare services: issues
and findings. International Journal of Productivity and Performance Management, 56(1), 7-24.
http://www.emeraldinsight.com/journals.htm?articleid=1585212&show=html
• Judith Wuest, Marilyn Merritt-Gray, Norma Dube´, Marilyn J. Hodgins, Jeannie Malcolm, Jo Ann Majerovich,
Kelly Scott-Storey, Marilyn Ford-Gilboe, Colleen Varcoe (2015) The Process, Outcomes, and Challenges of
Feasibility Studies Conducted in Partnership With Stakeholders: A Health Intervention for Women Survivors
of Intimate Partner Violence. 82-96 https://onlinelibrary.wiley.com/doi/pdf/10.1002/nur.21636
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